Computed tomography (“CT”) systems are often used to image the heart and cardiovasculature. The data for a given image may be collected from multiple cardiac cycles using multiple sectors. This creates a number of challenges. In an ideal case, the multiple sectors used to reconstruct the heart and cardiovasculature overlap for a zero Z location error between sectors. This, however, is not always the case. For a relatively low heart rate and high pitch, for example, the sectors used to reconstruct the heart and cardiovasculature do not always overlap, resulting in a relatively large Z location error between sectors and relatively poor slice-sensitive profiles. Because of this, the data collected from multiple cardiac cycles may be too far apart, resulting in poor image quality.
Thus, what is needed are systems and methods that generate high temporal resolution images for cardiac CT applications while addressing the problem of bad images by checking for these Z location errors between sectors and automatically backing-off to an alternative multi-sector algorithm when necessary (i.e., selecting an optimized maximum number of sectors to reconstruct), providing less Z location error. What is also needed are systems and methods that, based upon this Z location error, calculate the maximum number of sectors that should be used for reconstruction “on-the-fly” (i.e., on a per image basis across an entire series of images). Preferably, these systems and methods utilize the Recommended Protocol for Cardiac Reconstruction Algorithms.